Aspect Sentiment Triplet Extraction with Syntax-Semantics Graph Convolutional Network

Abstract In the traditional task of aspect sentiment triplet extraction, existing approaches typically focus on either syntactic or semantic features independently, failing to leverage the complementary integration of these two types of information. Although graph convolutional network-based approac...

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Autori principali:	Jingyun Zhang, Shuwei Xu, Xin Gao, Zhiwei Tang
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Springer 2025-07-01
Serie:	International Journal of Computational Intelligence Systems
Soggetti:	Aspect-based sentiment analysis Aspect sentiment triplet extraction Graph convolutional network Syntactic information and semantic information
Accesso online:	https://doi.org/10.1007/s44196-025-00900-w
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